Load expression data

## # A tibble: 6,639 x 4
## # Groups:   Gene [6,639]
##    Gene        RNA    RPF    TE
##    <chr>     <dbl>  <dbl> <dbl>
##  1 CNM01300  4001. 18299. 4.57 
##  2 CNM01080  8388.  8973. 1.07 
##  3 CNA07570  5785.  7163. 1.24 
##  4 CNG04360  3188.  7062. 2.22 
##  5 CNB02360  3708.  6972. 1.88 
##  6 CNA06350 15095.  6604. 0.437
##  7 CNC00700  2357.  6232. 2.64 
##  8 CNF03840 11379.  6188. 0.544
##  9 CNF02150 15472.  6159. 0.398
## 10 CNF03160  5121.  6125. 1.20 
## # ... with 6,629 more rows

We also calculated hiTrans_JEC21, the top 5% (330) translated genes by RPF TPM.

Ribosome occupancy mostly tracks RNA abundance

Load context data

## # A tibble: 6,639 x 19
##    Gene   aATG.context   aATG.pos d1.context  d1.posTSS d1.posATG d1.frame
##    <chr>  <chr>             <int> <chr>           <int>     <int>    <int>
##  1 CNA00… GACCCCCTTGTTA…       93 ATAGCTGGTC…       226      -133        1
##  2 CNA00… ATATTGCCTGAGA…      102 GTCCACCTTA…       163       -61        1
##  3 CNA00… GAACTATCAAGCA…      214 GAGGCTCCGC…       512      -298        1
##  4 CNA00… ATTTTCAACAGCA…       81 AGCAATATAC…       307      -226        1
##  5 CNA00… ACCGTGCACACCA…       76 GTATTCGGGG…       106       -30        0
##  6 CNA00… AATCATACCAAAA…      117 GCCCCTATCT…       186       -69        0
##  7 CNA00… CCGACTATAAAAA…       52 AACCGTGCTA…       112       -60        0
##  8 CNA00… CTTTCTCTTCAGA…       77 TGCTATAGCA…        98       -21        0
##  9 CNA00… TAATCACACAAGA…      330 CTCATCATCA…       391       -61        1
## 10 CNA00… AAAAAAAACGCGA…      146 ACTTGTCGAC…       184       -38        2
## # ... with 6,629 more rows, and 12 more variables: d2.context <chr>,
## #   d2.posTSS <int>, d2.posATG <int>, d2.frame <int>, u1.context <chr>,
## #   u1.posTSS <int>, u1.posATG <int>, u1.frame <int>, u2.context <chr>,
## #   u2.posTSS <int>, u2.posATG <int>, u2.frame <int>

Annotated ATGs have a Kozak consensus sequence

Highly translated Annotated ATGs have a Kozak consensus sequence

That’s for hiTrans_JEC21, the top 5% (330) translated genes by RPF TPM.

Cytoplasmic Ribosome Annotated ATGs have a Kozak consensus sequence

Upstream ATGs don’t have a consensus

First upstream ATG.

Downstream ATGs don’t have a consensus

First downstream ATG

Downstream ATGs in frame and highly translated don’t have a consensus

Except for 3rd-codon-position bias.

Calculate a wide and a narrow consensus sequence

Calculate motif score against the position weight matrix (pwm) for both narrow (-5 from ATG through to ATG) and wide (-9 from ATG to +3) kozak consensus motif. These motifs are taken from the top 5% highly translated genes.

Estimate the information content

Using the sequence logo, details on https://en.wikipedia.org/wiki/Sequence_logo

## # A tibble: 6 x 4
##   Genes    ATG   Width  Infon
##   <chr>    <chr> <chr>  <dbl>
## 1 All      aATG  narrow 0.987
## 2 HiTrans  aATG  narrow 3.01 
## 3 CytoRibo aATG  narrow 4.24 
## 4 All      d1ATG narrow 0.144
## 5 HiTrans  d1ATG narrow 0.340
## 6 CytoRibo d1ATG narrow 0.561

Information content in bits of highly-translated consensus (excluding 6 bits from ATG), narrow is 3.01, of wide is 4.71.

Calculate scores of aATG, dATG, uATG against Kozak consensus

We calculate scores using Biostrings::PWMscoreStartingAt.

The best description I could find of this method is: https://support.bioconductor.org/p/61520/

It is just the sum of the matrix product of the PWM with the sequence.

Write scores to file scores_kozak_JEC21.txt.

## # A tibble: 6,639 x 11
##    Gene     aATG.scorekn d1.scorekn u1.scorekn aATG.scorekw d1.scorekw
##    <chr>           <dbl>      <dbl>      <dbl>        <dbl>      <dbl>
##  1 CNA00010        0.737      0.723      0.968        0.662      0.707
##  2 CNA00020        0.814      0.934      0.868        0.735      0.892
##  3 CNA00030        0.875      0.698      0.804        0.874      0.689
##  4 CNA00040        0.887      0.802     NA            0.863      0.772
##  5 CNA00050        0.955      0.707     NA            0.839      0.707
##  6 CNA00060        1.000      0.889     NA            0.936      0.792
##  7 CNA00070        0.977      0.809     NA            0.893      0.670
##  8 CNA00075        0.791      0.922      0.735        0.799      0.835
##  9 CNA00080        0.933      0.923     NA            0.890      0.886
## 10 CNA00090        0.848      0.781     NA            0.875      0.699
## # ... with 6,629 more rows, and 5 more variables: u1.scorekw <dbl>,
## #   d1vsan <dbl>, u1vsan <dbl>, d1vsaw <dbl>, u1vsaw <dbl>

Plot against narrow consensus (-5 to ATG)

Plot against wide consensus (-9 to +3 from ATG)

Most dATG scores are less than aATG scores

Most u1ATG scores are less than aATG scores

For highly translated genes, most dATG scores are much less than aATG

Red: high dATG vs aATG Kozak score. Blue: highly translated. Purple: both.

dATG vs aATG ribosome occupancy depends on the context

For top 3315 / 50% of genes by mean RNA TPM.

dATG vs aATG ribosome occupancy depends on the context, geometric mean across reps

There is slight enrichment in high-score dATGs in frame near the aATG

Load predictions from mitofates

In input file JEC21_mitofates_26June2018.txt.

Genes with high dATG vs aATG score are enriched in mitochondrial presequences

However, mito-localized genes do not have a distinctive aATG context

It’s just a subset: the dual-localized ones.

uATGs are associated with lower absolute translation

uATGs are associated with lower translation efficiency

uATGs at least 20nt from start site

uATG vs aATG ribosome occupancy depends on the context

For top 3315 / 50% of genes by mean RNA TPM.

Back to table of contents

Load expression data

## # A tibble: 6,797 x 4
## # Groups:   Gene [6,797]
##    Gene          RNA    RPF    TE
##    <chr>       <dbl>  <dbl> <dbl>
##  1 CNAG_06125 10279. 20179. 1.96 
##  2 CNAG_06101  8672.  8471. 0.977
##  3 CNAG_05762  7396.  7528. 1.02 
##  4 CNAG_00779  3861.  7368. 1.91 
##  5 CNAG_03127  6257.  7184. 1.15 
##  6 CNAG_04011 13313.  6786. 0.510
##  7 CNAG_06222  6401.  6784. 1.06 
##  8 CNAG_01455 12683.  6580. 0.519
##  9 CNAG_05525  6978.  6456. 0.925
## 10 CNAG_03739  6383.  6394. 1.00 
## # ... with 6,787 more rows

We also calculated hiTrans_H99, the top 5% (330) translated genes by RPF TPM.

Ribosome occupancy mostly tracks RNA abundance

Load context data

## # A tibble: 6,797 x 19
##    Gene   aATG.context   aATG.pos d1.context  d1.posTSS d1.posATG d1.frame
##    <chr>  <chr>             <int> <chr>           <int>     <int>    <int>
##  1 CNAG_… TACTTACGCGACA…       70 AAATTCACTT…       100       -30        0
##  2 CNAG_… GAACTTCGATCAA…       52 TCTCCCGCCA…       114       -62        2
##  3 CNAG_… GTAGACTTACCTA…      346 CACGGGCATC…       395       -49        1
##  4 CNAG_… CACATACGTAACA…      214 CCGAACGGCG…       256       -42        0
##  5 CNAG_… GACTATACAAAAA…       55 GGAGGTGGGC…       163      -108        0
##  6 CNAG_… AACCATACAAAAA…       99 CAAAGCCATT…       259      -160        1
##  7 CNAG_… ACCGTGCACACCA…       75 GTATTCGGAA…       105       -30        0
##  8 CNAG_… GTTTTCAACAGCA…       73 CCCATCAGAA…       380      -307        1
##  9 CNAG_… GTACTATTGAACA…      206 GAGGCTCCGC…       513      -307        1
## 10 CNAG_… TACAAGCTTGAAA…       90 GGCCGCCTTA…       151       -61        1
## # ... with 6,787 more rows, and 12 more variables: d2.context <chr>,
## #   d2.posTSS <int>, d2.posATG <int>, d2.frame <int>, u1.context <chr>,
## #   u1.posTSS <int>, u1.posATG <int>, u1.frame <int>, u2.context <chr>,
## #   u2.posTSS <int>, u2.posATG <int>, u2.frame <int>

Annotated ATGs have a Kozak consensus sequence

Highly translated Annotated ATGs have a Kozak consensus sequence

That’s for hiTrans_H99, the top 5% (330) translated genes by RPF TPM.

Cytoplasmic Ribosome Annotated ATGs have a consensus sequence

Ideally would fix this more nicely.

Upstream ATGs don’t have a consensus

First upstream ATG.

Downstream ATGs don’t have a consensus

First downstream ATG

Downstream ATGs in frame and highly translated don’t have a consensus

Except for 3rd-codon-position bias.

Calculate a wide and a narrow consensus sequence

Calculate motif score against the position weight matrix (pwm) for both narrow (-5 from ATG through to ATG) and wide (-9 from ATG to +3) kozak consensus motif. These motifs are taken from the top 5% highly translated genes.

Estimate the information content

Using the sequence logo details on https://en.wikipedia.org/wiki/Sequence_logo

## # A tibble: 6 x 4
##   Genes    ATG   Width  Infon
##   <chr>    <chr> <chr>  <dbl>
## 1 All      aATG  narrow 0.550
## 2 HiTrans  aATG  narrow 3.12 
## 3 CytoRibo aATG  narrow 4.38 
## 4 All      d1ATG narrow 0.130
## 5 HiTrans  d1ATG narrow 0.267
## 6 CytoRibo d1ATG narrow 0.501

Information content in bits of highly-translated consensus (excluding 6 bits from ATG), narrow is 3.12, of wide is 4.9.

Calculate scores of aATG, dATG, uATG against Kozak consensus

Write scores to file scores_kozak_H99.txt.

## # A tibble: 6,797 x 11
##    Gene       aATG.scorekn d1.scorekn u1.scorekn aATG.scorekw d1.scorekw
##    <chr>             <dbl>      <dbl>      <dbl>        <dbl>      <dbl>
##  1 CNAG_00002        0.866      0.784      0.853        0.834      0.687
##  2 CNAG_00003        0.833      0.847     NA            0.792      0.808
##  3 CNAG_00004        0.794      0.795     NA            0.759      0.665
##  4 CNAG_00005        0.880      0.752      0.855        0.892      0.659
##  5 CNAG_00006        0.978      0.727     NA            0.872      0.624
##  6 CNAG_00007        0.978      0.708     NA            0.916      0.662
##  7 CNAG_00008        0.960      0.819     NA            0.847      0.798
##  8 CNAG_00009        0.876      0.798     NA            0.864      0.783
##  9 CNAG_00010        0.896      0.796      0.822        0.849      0.756
## 10 CNAG_00011        0.878      0.937      0.691        0.743      0.862
## # ... with 6,787 more rows, and 5 more variables: u1.scorekw <dbl>,
## #   d1vsan <dbl>, u1vsan <dbl>, d1vsaw <dbl>, u1vsaw <dbl>

Plot against narrow consensus (-5 to ATG)

Plot against wide consensus (-9 to +3 from ATG)

Most dATG scores are less than aATG scores

Most u1ATG scores are less than aATG scores

For highly translated genes, most dATG scores are much less than aATG

dATG vs aATG ribosome occupancy depends on the context

For top 3315 / 50% of genes by mean RNA TPM.

dATG vs aATG ribosome occupancy and score, geometric mean across reps

Load predictions from mitofates

In input file H99_mitofates_26June2018.txt.

Genes with high dATG vs aATG score are enriched in mitochondrial presequences

However, mito-localized genes do not have a distinctive aATG context

It’s just a subset: the dual-localized ones.

uATGs are associated with lower absolute translation

uATGs are associated with lower translation efficiency

uATGs at least 20nt from start site

uATG vs aATG ribosome occupancy depends on the context

For top 3315 / 50% of genes by mean RNA TPM.

Back to table of contents

RNA Abundance

Ribosome Occupancy

Translation efficiency, no threshold

Translation efficiency, filtered by top 50% of expression

dATG in frame with ATG

Saved to file dvsaATG_highdiffn_inframe_cc.txt.

## # A tibble: 44 x 6
##    H99        JEC21    a.skn.H99 d.skn.H99 a.skn.JEC21 d.skn.JEC21
##    <chr>      <chr>        <dbl>     <dbl>       <dbl>       <dbl>
##  1 CNAG_07473 CNB01880     0.606     0.969       0.625       0.894
##  2 CNAG_07776 CNI00670     0.700     0.993       0.710       0.990
##  3 CNAG_00165 CNA01530     0.675     0.957       0.675       0.956
##  4 CNAG_02545 CNE00210     0.666     0.940       0.682       0.943
##  5 CNAG_07801 CNL06190     0.675     0.978       0.685       0.904
##  6 CNAG_01544 CNC06400     0.727     0.978       0.723       0.978
##  7 CNAG_03953 CNB04410     0.692     0.991       0.741       0.947
##  8 CNAG_04179 CNI03160     0.709     0.991       0.725       0.947
##  9 CNAG_05722 CNF02520     0.668     0.912       0.675       0.918
## 10 CNAG_02431 CNE01260     0.727     0.999       0.731       0.943
## 11 CNAG_02880 CNC04930     0.666     0.912       0.682       0.911
## 12 CNAG_03996 CNB04810     0.666     0.899       0.625       0.848
## 13 CNAG_00517 CNA04990     0.732     0.934       0.702       0.942
## 14 CNAG_02259 CNE02870     0.676     0.978       0.695       0.835
## 15 CNAG_03396 CNG01890     0.632     0.861       0.642       0.854
## 16 CNAG_00086 CNA00760     0.736     0.957       0.742       0.956
## 17 CNAG_07873 CNH00360     0.733     0.948       0.749       0.946
## 18 CNAG_04219 CNI03610     0.779     0.978       0.771       0.978
## 19 CNAG_04604 CNJ00430     0.789     0.990       0.797       0.990
## 20 CNAG_00026 CNA00190     0.726     0.957       0.720       0.877
## # ... with 24 more rows

dATG out of frame

Saved to file dvsaATG_highdiffn_outframe_cc.txt.

## # A tibble: 14 x 6
##    H99        JEC21    a.skn.H99 d.skn.H99 a.skn.JEC21 d.skn.JEC21
##    <chr>      <chr>        <dbl>     <dbl>       <dbl>       <dbl>
##  1 CNAG_06278 CNN00160     0.699     0.991       0.724       0.989
##  2 CNAG_04054 CNB05380     0.717     0.978       0.723       0.978
##  3 CNAG_02894 CNC05065     0.783     0.978       0.798       0.978
##  4 CNAG_06006 CNM00150     0.715     0.934       0.781       0.933
##  5 CNAG_02809 CNC04270     0.801     0.978       0.792       0.978
##  6 CNAG_03008 CNC06190     0.827     0.999       0.817       1    
##  7 CNAG_03370 CNG02120     0.803     0.969       0.795       0.968
##  8 CNAG_01667 CNC01780     0.842     0.990       0.837       0.990
##  9 CNAG_00784 CNA07610     0.692     0.842       0.696       0.837
## 10 CNAG_02578 CNK00690     0.826     0.945       0.791       0.944
## 11 CNAG_01241 CND03590     0.757     0.883       0.761       0.897
## 12 CNAG_07780 CNI00090     0.876     0.999       0.867       1    
## 13 CNAG_01270 CND03900     0.668     0.791       0.675       0.791
## 14 CNAG_03839 CNB03280     0.824     0.941       0.822       0.942

• CNN00160 two-component-like sensor kinase TCO7
• CNB05380 SUI1/eIF1, translation initiation factor.
• CNC06190 has a domain conserved with eIF2.
• CNG02120 freqenin calcium-binding protein, FRQ1 homolog
• CNC05065/CNM00150/CNC04270/CNC06190/CNA07610/CND03900, all hypothetical or uncharacterized.
• CNC01780 prenyltransferase, COQ2 homolog
• CNK00690 regulation of meiosis-related, PCH2 homolog
• CND03590 protein phosphatase I nuclear regulatory subunit, SDS22 homolog
• CNI00090 farnesyltranstransferase, BTS1 homolog
• CND03900 has a W2 eIF4-gamma/eIF5/eIF2-epsilon - like domain
• CNB03280 mRNA transcription modulator, CCR4-NOT ubiquitin ligase subunit MOT2 homolog.

Genes with very different aATG scores, JEC21 vs H99

Filtered for enough RNA (top 50%)

## # A tibble: 120 x 6
##    H99        JEC21    a.skn.H99 d.skn.H99 a.skn.JEC21 d.skn.JEC21
##    <chr>      <chr>        <dbl>     <dbl>       <dbl>       <dbl>
##  1 CNAG_04147 CNI02850     0.644     0.984       0.946       0.890
##  2 CNAG_06000 CNM00090     0.686     0.913       0.966       0.757
##  3 CNAG_03486 CNG01060     0.703     0.967       0.966       0.778
##  4 CNAG_06196 CNM01950     0.732     0.634       0.990       0.743
##  5 CNAG_06353 CNN00820     0.658     0.904       0.904       0.837
##  6 CNAG_06446 CNN01710     0.764     0.999       1           0.628
##  7 CNAG_01092 CND02180     0.689     0.925       0.922       0.877
##  8 CNAG_01188 CND03130     0.651     0.791       0.883       0.732
##  9 CNAG_05678 CNF02960     0.689     0.910       0.917       0.932
## 10 CNAG_07645 CNE03115     0.660     0.754       0.887       0.685
## # ... with 110 more rows

## # A tibble: 120 x 6
##    H99        JEC21    a.skn.H99 d.skn.H99 a.skn.JEC21 d.skn.JEC21
##    <chr>      <chr>        <dbl>     <dbl>       <dbl>       <dbl>
##  1 CNAG_00529 CNA05110     0.948     0.811       0.702       0.887
##  2 CNAG_03410 CNG01740     0.990     0.741       0.754       0.990
##  3 CNAG_04089 CNB05680     0.967     0.817       0.742       0.891
##  4 CNAG_04751 CNJ01820     0.960     0.860       0.737       0.922
##  5 CNAG_04899 CNJ03230     0.948     0.783       0.736       0.968
##  6 CNAG_02703 CNK01910     0.894     0.747       0.696       0.883
##  7 CNAG_03638 CNB01390     0.909     0.793       0.718       0.666
##  8 CNAG_05504 CNH01580     0.967     0.819       0.786       0.849
##  9 CNAG_05692 CNF02820     0.923     0.785       0.745       0.849
## 10 CNAG_07609 CNC03180     0.967     0.890       0.790       0.838
## # ... with 110 more rows

Many of these have the expected structure where homologs differ only at the N-terminus. There appears to be a swap between a near-ATG start codon, and a poor-context ATG, between the species.

Higher aATG score in JEC21:

• CNAG_04147/CNI02850, putative RNA helicase RRP3 homolog
• CNAG_06000/CNM00090, putative glycoprotein
• CNAG_03486/CNG01060, peptidylprolyl isomerase, Scer has CPR2/CPR5 homolgs localized to ER and vacuole.
• CNAG_06353/CNN00820, tRNA pseudouridine synthase, exciting, CNAG_06353 has weak mito loc seq, Scer has PUS1/PUS2 nuc/mito homologs.
• CNAG_06446/CNN01710, mitochondrial splicing suppressor Mss51 homolog, clear mito preseq in both.
• CNAG_01092/CND02180, hypothetical protein conserved in crypto, mito preseq in both
• CNAG_01188/CND03130, ATGATG start in H99, not interesting
• CNAG_05678/CNF02960, putative transmembrane protein involved in ammonia production.
• CNAG_07645/CNE03115 Autophagy protein Atg12, H99 CNAG_07645 has non-homologous annotated N-terminal extension that seems improbably.

Higher aATG score in H99:

• CNAG_00529/CNA05110, sulfite transporter, Scer Ssu1 homolog.
• CNAG_03410/CNG01740, upstream ATG in JEC21 close to TSS, prob not real
• CNAG_04089/CNB05680, again upstream ATG in JEC21 close to TSS, prob not real. Note that CNAG_03410/CNAG_04089 are paralogs
• CNAG_04751/CNJ01820, hypothetical protein conserved in tremellomycetes.
• CNAG_02703/CNK01910, hypothetical protein conserved in tremellomycetes.
• CNAG_03638/CNB01390, identical ATG context in fungidb, check.
• CNAG_05504/CNH01580, Iah1, pattern unclear, JEC21 just has poor start codons.
• CNAG_05692/CNF02820, sphinganine kinase, Scer YSR3/LCB2 homolog.
• CNAG_07609/CNC03180, putative RNA helicase, weak start context in JEC21 predicts less protein in cell. Or most translation initiation is from much later ATG? DDX51/DBP6 homolog.

These look like mostly misannotated in one strain, or not interesting. Is the upstream start codon in one strain actually used? Check for ribosome footprints and for other features (homology, mito localization seq). It would be nice to have an additional filter here.

Non-canonical aATG motif from the 9 tRNA synthetases with poor Kozak score and in-frame high-score dATG

dATG motif is canonical from those 9 tRNA synthetases

Calculate unusual tRNA synthetase scores and consensus table

Output to file scores_kozak_unusual_mito_cc.txt.

## # A tibble: 6,341 x 14
##    H99   JEC21 aATG.scorekn.H99 d1.scorekn.H99 u1.scorekn.H99
##    <chr> <chr>            <dbl>          <dbl>          <dbl>
##  1 CNAG… CND0…            0.990          0.794         NA    
##  2 CNAG… CNH0…            0.835          0.918         NA    
##  3 CNAG… CNH0…            0.877          0.855          0.842
##  4 CNAG… CNB0…            0.902          0.791          0.795
##  5 CNAG… CNF0…            0.846          0.690         NA    
##  6 CNAG… CNA0…            0.957          1              0.912
##  7 CNAG… CNK0…            0.844          0.785         NA    
##  8 CNAG… CNB0…            0.967          0.732         NA    
##  9 CNAG… CNM0…            0.946          0.752         NA    
## 10 CNAG… CNG0…            0.954          0.890          0.813
## # ... with 6,331 more rows, and 9 more variables:
## #   aATG.scorekn.JEC21 <dbl>, d1.scorekn.JEC21 <dbl>,
## #   u1.scorekn.JEC21 <dbl>, aATG.scoreUn.H99 <dbl>,
## #   aATG.scoreUn.JEC21 <dbl>, Prob_mito.H99 <dbl>, Pred_mito.H99 <fct>,
## #   Prob_mito.JEC21 <dbl>, Pred_mito.JEC21 <fct>

Genes with high score against utRS motif are often dual-localized.

## # A tibble: 19 x 6
##    Gene     a.scorekn d.scorekn a.scoreUn aATG.context         Prob_preseq
##    <chr>        <dbl>     <dbl>     <dbl> <chr>                      <dbl>
##  1 CNB01880     0.625     0.894     0.983 CGATAACGGTGTATGCTCC…       0.967
##  2 CNA01530     0.675     0.956     0.966 AACAAACATTGTATGCGTT…       0.299
##  3 CNE00210     0.682     0.943     0.973 AAAGAAAGGTGCATGAACA…       0.9  
##  4 CNL06190     0.685     0.904     0.966 ATCTTCGTTTGTATGCCAA…       0.443
##  5 CNC06400     0.723     0.978     0.952 CCCAGCAGCTTTATGCTCC…       0.995
##  6 CNI03160     0.725     0.947     0.956 TCCAGATTGTGCATGCTCA…       0.985
##  7 CNF02520     0.675     0.918     0.966 ACACGACATTGTATGCTCT…       0.989
##  8 CNC04930     0.682     0.911     0.973 GAAAAGAGGTGCATGTCAT…       0.507
##  9 CNB04810     0.625     0.848     0.983 ATCAACAGGTGTATGCCTG…       0    
## 10 CNG01890     0.642     0.854     0.983 GGAAGGCGTTGTATGATCA…       0.777
## 11 CNA00760     0.742     0.956     0.956 AAACATCTTTGCATGCCTC…       0.546
## 12 CNJ00430     0.797     0.990     0.973 TCCCACCCCTGCATGCCCC…       0.881
## 13 CNB00900     0.797     0.980     0.973 TCCAGCATCTGCATGCTAC…       0.994
## 14 CNB05640     0.758     0.956     0.925 CCCGACAGATTCATGCTCC…       0.423
## 15 CNB01800     0.823     0.999     0.925 TTCTTCTTCTTCATGTTCA…       0.987
## 16 CNB04990     0.801     0.976     0.908 CTGGCTATATTCATGCCTT…       0.214
## 17 CNB01775     0.757     0.956     0.935 TAGGGACACTTTATGAGGA…       0.026
## 18 CNB04910     0.823     0.966     0.925 TCCTTCCTCTTCATGCTCT…       0.986
## 19 CND00900     0.712     0.835     0.918 GAAGCTGCTTTTATGATGT…       0

These genes are:

- CNB01880, valine tRNA-ligase*
- CNA01530, S-methyl-5-thioadenosine phosphorylase MEU1 homolog
- CNE00210, inorganic diphosphatase IPP1 homolog
- CNL06190, putative aldo-keto reductase GCY1/YCR1 homolog
- CNC06400, histidine-tRNA ligase*
- CNI03160, lysine-tRNA ligase*
- CNF02520, alanine-tRNA ligase*
- CNC04930, YchF-family translational regulator, OLA1 homolog
- CNB04810, guanosine-diphosphatase, GDA1 homolog
- CNG01890, NAD+ diphosphatase, NPY1 homolog
- CNA00760, tRNA (guanine-N2-)-methyltransferase, TRM1 homolog
- CNJ00430, tryptophan-tRNA ligase*
- CNB00900, cysteine-tRNA ligase*
- CNB05640, proline-tRNA ligase*
- CNB01800, macrolide-binding protein FKBP12, FPR1 homolog
- CNB04990, Methionine-R-sulfoxide reductase, MXR2 homolog
- CNB01775, hypothetical Acylphosphatase family protein
- CNB04910, putative aminopeptidase, AAP1/APE2 homolog
- CND00900, DEAH-box RNA helicase, PRP22 homolog

* these genes were used to construct the consensus sequence.

In S. cerevisiae: TRM1 is dual-localized to mito and cyto. APE2 is dual mito/cyto localized. GDA1 is golgi-localized. NPY1 is peroxisome and cyto localized. GCY1 and YCR1 are nucleus/cytoplasm localized. FPR1 is multiply localized. MXR2 is mito localized.

CND00900 has two adjacent ATGs to start (GCTTTTATGATGTCC), the 2nd of which gives the good context score due to the A in the first.

aATG motif scores, comparing Kozak vs non-canonical tRS

In JEC21 only. Red: high dATG vs aATG Kozak score. Blue: highly translated. Purple: both.

Note that many points are overplotted at the same y-values because the score is mostly quantized on a small number of values.

High utRS score is enriched in mito-localized genes

Note we do not control for expression or any other potential factor affecting ATG context.

To-do: Analysis of other tRNA synthetases

For example, CNM01290, Leucine-tRNA synthetase, was on a previous version of this list. It has good kozak score at aATG and conserved out-of-frame dATG.

dATG score high compared aATG and dATG out of frame, 14 genes

File dvsaATG_highdiffn_outframe_cc.txt.

No significant GO terms.

dATG score high compared aATG and dATG in frame, 44 genes

File dvsaATG_highdiffn_inframe_cc.txt.

Enriched in Biological processes:

• tRNA aminoacylation for protein translation< translation < protein metabolic process < primary metabolic process < metabolic process
• tRNA metabolic process < RNA metabolic process < nucleobase-containing compound metabolic process
• Unclassified

Molecular Function:

• aminoacyl-tRNA ligase activity < ligase activity < catalytic activity

Cellular Component:

• cytosol < cytoplasm < intracellular < cell part

Highly translated, 291 genes

File hiTrans_cc.txt.

Enriched BPs include:

• oxidative phosphorylation
• glycolysis
• translation
• protein folding
• cation transport
• mitochondrial transport

Enriched MFs include:

• transmembrane transporter activity
• structural constituent of ribosome
• translation elongation factor activity

Enriched CCs include:

• proton-transporting ATP synthase complex
• ribosome
• mitochondrial inner membrane

High translation efficiency, 174 genes

File hiTE_cc.txt.

Enriched BPs include:

• pentose-phosphate shunt < monosaccharide metabolic process
• tRNA aminoacylation for protein translation < translation
• acyl-CoA metabolic process
• tricarboxylic acid cycle
• cellular amino acid biosynthetic process
• nuclear transport

Enriched MFs include:

• translation elongation factor activity
• translation initiation factor activity
• aminoacyl-tRNA ligase activity

Enriched CCs include:

• cytosol < cytoplasm

Low translation efficiency, 284 genes

File loTE_cc.txt.

Enriched BPs include:

• anion transport

Enriched MFs, no sig. results.

Enriched CCs, no sig. results.

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